code: def test_forward(self, cfg_file):
      model_cfg = get_detector_cfg(cfg_file)
      model = MODELS.build(model_cfg)
      inputs = torch.rand(1, 4, 3, 256, 128)
      data_samples = [
          ReIDDataSample().set_gt_label(label) for label in (0, 0, 1, 1)
      ]
  
      # test mode='tensor'
      feats = model(inputs, mode="tensor")
      assert feats.shape == (4, 128)
  
      # test mode='loss'
      losses = model(inputs, data_samples, mode="loss")
      assert losses.keys() == {
          "triplet_loss",
          "ce_loss",
          "accuracy_top-1",
      }
      assert losses["ce_loss"].item() > 0
      assert losses["triplet_loss"].item() > 0
  
      # test mode='predict'
      predictions = model(inputs, data_samples, mode="predict")
      for pred in predictions:
          assert isinstance(pred, ReIDDataSample)
          assert isinstance(pred.pred_feature, torch.Tensor)
          assert isinstance(pred.gt_label.label, torch.Tensor)
          assert pred.pred_feature.shape == (128,)
  
file_path: mmdetection/tests/test_models/test_reid/test_base_reid.py
imports: from unittest import TestCase
  import torch
  from parameterized import parameterized
  from mmdet.registry import MODELS
  from mmdet.structures import ReIDDataSample
  from mmdet.testing import get_detector_cfg
  from mmdet.utils import register_all_modules
label_desc: Use image node_id 2 for calling the TestBaseReID obj's underlying member method code with example usage: obj.test_forward(cfg_file) without return types